论文标题
错误指定和渐近最小的最大变化最快的更改诊断
Misspecified and Asymptotically Minimax Robust Quickest Change Diagnosis
论文作者
论文摘要
研究了快速诊断随机过程中未知变化的问题。我们建立了针对与该过程不同的变化的刻痕诊断算法的性能建立新的界限，并在几乎没有错误的警报和错误隔离的渐近状态下摆姿势并解决了新的最大变化诊断问题。模拟表明，我们的渐近鲁棒解决方案为广义似然比算法提供了一种计算有效的替代方案。
The problem of quickly diagnosing an unknown change in a stochastic process is studied. We establish novel bounds on the performance of misspecified diagnosis algorithms designed for changes that differ from those of the process, and pose and solve a new robust quickest change diagnosis problem in the asymptotic regime of few false alarms and false isolations. Simulations suggest that our asymptotically robust solution offers a computationally efficient alternative to generalised likelihood ratio algorithms.
